Ever since I started working Opencl WUs, I noticed that I get them in drips & drabs. Out of the 44 AP tasks that are now processing only 4 are tagged for the GPU. How does the scheduler differentiate between which get tagged for CPU work vs GPU work? And, is there a way other than stopping all CPU WUs of having the scheduler send out more GPU work?
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you could use the rescheduler to move the WU's to the GPU or if you don't want AP work on your CPU, don't include the CPU AP portion in your app_info
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In a rich man's house there is no place to spit but his face.
Diogenes Of Sinope

Something like that - I don't look at the points per hour very often.
I don't have any cores reserved on either of my GPU rigs. I did try it once on the one with a 460, and it might have sped up the GPU by a couple of percent, but I lost more by not having the credit from all six CPU cores. The CPU is a 6 core Phenom, and as I don't have any Intel based crunchers I can't comment on any advantages or otherwise by having a core reserved on say an i7.
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Bob Smith
Member of Seti PIPPS (Pluto is a Planet Protest Society)
Somewhere in the (un)known Universe?

Check out my i7/950 -- it is running 1 x GTX660SC/2Gb & 1 x GTX460SE/1Gb. Both are running Lunatics _x41zc cuda 5.0 @ 3 each & Opencl _r1761 @ 1 each. CPU MB tasks run an avg of 11 hrs, GPU MB avg 20-25 min, & AP Opencl avg 45 min. Normally I run at 80% of processors ( 6 cores). Opencl will explicitly reserve 1 core for each task running, and it will release it when the task is finished. Not the fastest in the Seti universe, but I am happy with the results so far. The machine is a Win7/64-bit running BOINC 7.0.48 and nVidia 313.96.
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Rob you are very slow compared to other 460´s.
Do you check you results.
13000 seconds instead of 3500.
You would benefit a lot reserving a core.

Hi Mike,

The 13500 is from my CPU (6 units at that time). Rob is doing about 3 tasks in an hour (3600s).

Do you know how many seconds CPU time it takes for a task that finishes in an hour?

Not quite what I said, my figure was based on an extrapolation of what my 460 delivers and knowing how much faster a 660 is than a 460 (I should have made that a bit clearer)
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Bob Smith
Member of Seti PIPPS (Pluto is a Planet Protest Society)
Somewhere in the (un)known Universe?

Rob you are very slow compared to other 460´s.
Do you check you results.
13000 seconds instead of 3500.
You would benefit a lot reserving a core.

Hi Mike,

The 13500 is from my CPU (6 units at that time). Rob is doing about 3 tasks in an hour (3600s).

Do you know how many seconds CPU time it takes for a task that finishes in an hour?

No i checked Robs host.
Just today 3 WUs longer than 13000 seconds.
Thats because driver hangs because of lack of CPU cycles.
Wouldn`t happen with a free CPU core.
He is wasting GPU cycles.
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Check out my i7/950 -- it is running 1 x GTX660SC/2Gb & 1 x GTX460SE/1Gb. Both are running Lunatics _x41zc cuda 5.0 @ 3 each & Opencl _r1761 @ 1 each. CPU MB tasks run an avg of 11 hrs, GPU MB avg 20-25 min, & AP Opencl avg 45 min. Normally I run at 80% of processors ( 6 cores). Opencl will explicitly reserve 1 core for each task running, and it will release it when the task is finished. Not the fastest in the Seti universe, but I am happy with the results so far. The machine is a Win7/64-bit running BOINC 7.0.48 and nVidia 313.96.

Thank You Cliff,

I'll take a look at your computer(s) (the i7/950) on sunday.

Did I understand correctly: You are doing 3 GPU MB (cuda) and one GPU AP (opencl) at a time on both cards and an additional 4-6 CPU tasks. (4 when runnig AP opencl on both cards)

I did try running with one core feeding the GPU about 6 months ago (with the current hardware and software set up) and the overall throughput (total tasks per hour)was less with one core set aside for feeding the GPU than having the default settings where there is a "free for all". I have no doubt that for other CPU+GPU configurations the results would be different.

(I have run GPU-X on a few occasions, and the load time (time when the GPU is essential idle, is only a few seconds - between 5 and 10, not a lot when the run time is way over a thousand).
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Bob Smith
Member of Seti PIPPS (Pluto is a Planet Protest Society)
Somewhere in the (un)known Universe?

I did try running with one core feeding the GPU about 6 months ago (with the current hardware and software set up) and the overall throughput (total tasks per hour)was less with one core set aside for feeding the GPU than having the default settings where there is a "free for all". I have no doubt that for other CPU+GPU configurations the results would be different.

(I have run GPU-X on a few occasions, and the load time (time when the GPU is essential idle, is only a few seconds - between 5 and 10, not a lot when the run time is way over a thousand).

Thats just because 1 core is not enough on AMD machines.

I finnish 2 APs in less an hour.
Thats ~3000 seconds.
You finnish in about 13000 - 15000 seconds.
Do you see the difference ?
I`m running APs over 2 years now and am fully aware of each conditions.

Check out my i7/950 -- it is running 1 x GTX660SC/2Gb & 1 x GTX460SE/1Gb. Both are running Lunatics _x41zc cuda 5.0 @ 3 each & Opencl _r1761 @ 1 each. CPU MB tasks run an avg of 11 hrs, GPU MB avg 20-25 min, & AP Opencl avg 45 min. Normally I run at 80% of processors ( 6 cores). Opencl will explicitly reserve 1 core for each task running, and it will release it when the task is finished. Not the fastest in the Seti universe, but I am happy with the results so far. The machine is a Win7/64-bit running BOINC 7.0.48 and nVidia 313.96.

Thank You Cliff,

I'll take a look at your computer(s) (the i7/950) on sunday.

Did I understand correctly: You are doing 3 GPU MB (cuda) and one GPU AP (opencl) at a time on both cards and an additional 4-6 CPU tasks. (4 when runnig AP opencl on both cards)

Now it is time for me to go to sleep. It is 1.00 AM in Finland.

Happy Crunching!

Yep, that's what I do! This is all running with defaults except with the count for the cuda tasks. If anyone knows how to tweak the apps to get more out of them let me know.
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